Anton Thielmann
Anton Thielmann
Data Science & Statistics, Georg-August-University Göttingen, Clausthal University of Technology
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Zitiert von
Zitiert von
Predicting tree species from 3D laser scanning point clouds using deep learning
D Seidel, P Annighöfer, A Thielman, QE Seifert, JH Thauer, J Glatthorn, ...
Frontiers in Plant Science 12, 635440, 2021
Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data
C Weisser, C Gerloff, A Thielmann, A Python, A Reuter, T Kneib, B Säfken
Computational statistics 38 (2), 647-674, 2023
Unsupervised document classification integrating web scraping, one-class SVM and LDA topic modelling
A Thielmann, C Weisser, A Krenz, B Säfken
Journal of Applied Statistics 50 (3), 574-591, 2023
One-class support vector machine and LDA topic model integration—Evidence for AI patents
A Thielmann, C Weisser, A Krenz
Soft computing: Biomedical and related applications, 263-272, 2021
Structural neural additive models: Enhanced interpretable machine learning
M Luber, A Thielmann, B Säfken
arXiv preprint arXiv:2302.09275, 2023
Coherence based document clustering
A Thielmann, C Weisser, T Kneib, B Säfken
2023 IEEE 17th International Conference on Semantic Computing (ICSC), 9-16, 2023
Neural additive models for location scale and shape: A framework for interpretable neural regression beyond the mean
AF Thielmann, RM Kruse, T Kneib, B Säfken
International Conference on Artificial Intelligence and Statistics, 1783-1791, 2024
Community-detection via hashtag-graphs for semi-supervised NMF topic models
M Luber, A Thielmann, C Weisser, B Säfken
arXiv preprint arXiv:2111.10401, 2021
Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence
A Thielmann, Q Seifert, A Reuter, E Bergherr, B Säfken
arXiv preprint arXiv:2303.17324, 2023
Penalized regression splines in mixture density networks
QE Seifert, A Thielmann, E Bergherr, B Säfken, J Zierk, M Rauh, T Hepp
Human in the loop: How to effectively create coherent topics by manually labeling only a few documents per class
A Thielmann, C Weisser, B Säfken
arXiv preprint arXiv:2212.09422, 2022
Topics in the Haystack: Enhancing Topic Quality through Corpus Expansion
A Thielmann, A Reuter, Q Seifert, E Bergherr, B Säfken
Computational Linguistics, 1-36, 2024
Audolab: automatic document labelling and classification for extremely unbalanced data
A Tillmann, A Thielmann, G Kant, C Weisser, B Säfken, A Silbersdorff, ...
Journal of Open Source Software 6 (66), 3719, 2021
GPTopic: Dynamic and Interactive Topic Representations
A Reuter, A Thielmann, C Weisser, S Fischer, B Säfken
arXiv preprint arXiv:2403.03628, 2024
Probabilistic Topic Modelling with Transformer Representations
A Reuter, A Thielmann, C Weisser, B Säfken, T Kneib
arXiv preprint arXiv:2403.03737, 2024
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
A Thielmann, RM Kruse, T Kneib, B Säfken
arXiv preprint arXiv:2301.11862, 2023
Sign Language Recognition using Regularized Convolutional Neural Networks
A Thielmann, Q Seifert, J Lichter
Reading Processing Applying, 53, 2020
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